User-Centred Social Media

Our group participates in the DFG-funded Research Training Group (Graduate School) “User-Centred Social Media” which aims at developing new models and methods for analyzing, designing and evaluating social media from a user-centred perspective. The main research fields in the RTG are modelling and understanding user behavior, social media engineering, and social media analytics. The program is an interdisciplinary endeavor located in our University department that fully integrates researchers from computer science and psychology. We contribute to the RTG with two PhD topics which lie in the areas of trustworthy recommendations based on social media sources and health-related behavioural interventions.

Modelling and Understanding User Behavior

Publications

Social Media Engineering

Publications

Contact

Catalin-Mihai Barbu

Researcher

Helma Torkamaan

Researcher

Jürgen Ziegler

Full Professor

Related publications

Trust-Related Effects of Expertise and Similarity Cues in Human-Generated Recommendations

Kunkel, J., Donkers, T., Barbu, C.-M., & Ziegler, J. (2018). In 2nd Workshop on Theory-Informed User Modeling for Tailoring and Personalizing Interfaces (HUMANIZE), 11 March 2018, Tokyo, Japan.

A Taxonomy of Mood Research and Its Applications in Computer Science

Torkamaan, H., & Ziegler, J. (2017). In 2017 Seventh International Conference on Affective Computing and Intelligent Interaction (ACII), San Antonio, Texas, October 23-26.

Co-Staying: a Social Network for Increasing the Trustworthiness of Hotel Recommendations

Barbu, C.-M., & Ziegler, J. (2017). In J. Neidhardt, D. Fesenmaier, T. Kuflik, & W. Wörndl (Eds.), RecTour 2017: 2nd Workshop on Recommenders in Tourism : Proceedings of the 2nd Workshop on Recommenders in Tourism co-located with 11th ACM Conference on Recommender Systems (RecSys 2017) Como, Italy, August 27, 2017 (Vol. 1906, pp. 35–39).

Users’ Choices About Hotel Booking: Cues for Personalizing the Presentation of Recommendations

Barbu, C.-M., & Ziegler, J. (2017). In T. Domonkos & P. Pu (Eds.), Poster Proceeding of ACM Recsys 2017: Proceedings of the Poster Track of the 11th ACM Conference on Recommender Systems (RecSys 2017) Como, Italy, August 28, 2017 (Vol. 1905, pp. 44–45).

User Model Dimensions for Personalizing the Presentation of Recommendations

Barbu, C.-M., & Ziegler, J. (2017). In P. Brusilovsky, M. de Gemmis, A. Felfernig, P. Lops, J. O’Donovan, N. Tintarev, & C. M. Willemsen (Eds.), IntRS 2017: Interfaces and Human Decision Making for Recommender Systems : Proceedings of the 4th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems co-located with ACM Conference on Recommender Systems (RecSys 2017) (Vol. 1884, pp. 20–23).

Enhancing an Interactive Recommendation System with Review-based Information Filtering

Feuerbach, J., Loepp, B., Barbu, C.-M., & Ziegler, J. (2017). In Proceedings of the 4th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems (IntRS ’17) (Vol. 1884, pp. 2–9).

Increasing the Trustworthiness of Recommendations by Exploiting Social Media Sources

Barbu, C.-M. (2016). In Proceedings of the 10th ACM Conference on Recommender Systems (pp. 447–450). New York, NY, USA: ACM.

Implementation of Emotional-Aware Computer Systems Using Typical Input Devices

Bakhtiyari, K., Taghavi, M., & Husain, H. (2014). In N. T. Nguyen, B. Attachoo, B. Trawiński, & K. Somboonviwat (Eds.), Implementation of Emotional-Aware Computer Systems Using Typical Input Devices (pp. 364–374). Cham: Springer International Publishing.

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Related projects

UCSM

User-controllable methods for generating trustworthy recommendations from social media sources